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Optimization for the sum of finite functions over the solution set of split equality optimization problems with applications. (English) Zbl 1480.47090

Summary: In this paper, we adopt an iterative approach to solve the class of optimization problem for the sum of finite functions over split equality optimization problems for the sum of two functions. This type of problem contains many optimization problems, and bilevel problems, as well as split equality problems, and split feasibility problems as special cases. Here, we are able to establish a strong convergence theorem for an iterative method for solving this problem. As consequences of this convergence theorem, we study the following problems: optimization for the sum of finite functions over the common solution set of optimization problems for the sum of two functions; optimization for the sum of finite functions; optimization for the sum of finite functions with split equality inconsistent feasibility constraints; optimization for the sum of finite functions over the solution set for split equality constrained quadratic signal recovery problem; optimization for the sum of finite functions over the solution set of generalized split equality multiple set feasibility problem, and optimization for the sum of finite functions over the solution set of split equality linear equations problem. We use simultaneous iteration to establish strong convergence theorems for these problems. Our results generalize and improve many existing theorems for these types of problems in the literature and will have applications in nonlinear analysis, optimization problems and signal processing problems.

MSC:

47J25 Iterative procedures involving nonlinear operators
47H06 Nonlinear accretive operators, dissipative operators, etc.
47H09 Contraction-type mappings, nonexpansive mappings, \(A\)-proper mappings, etc.
65K15 Numerical methods for variational inequalities and related problems
90C35 Programming involving graphs or networks
90C25 Convex programming
Full Text: DOI

References:

[1] Censor, Y., Elfving, T.: A multi projection algorithm using Bregman projection in a product space. Numer. Algorithms 8, 221-239 (1994) · Zbl 0828.65065 · doi:10.1007/BF02142692
[2] Moudafi, A.: A relaxed alternating CQ algorithm for convex feasibility problems. Nonlinear Anal. 79(2013), 117-121 (2013) · Zbl 1256.49044 · doi:10.1016/j.na.2012.11.013
[3] Chuang, C.S., Yu, Z.T., Lin, L.J.: Mathematical programming for the sum of two convex functions with applications to lasso problems, split feasibility problems and image deblurring problem. Fixed Point Theory Appl. 2015, 143 (2015) · Zbl 1338.90405 · doi:10.1186/s13663-015-0388-0
[4] Lin, L.J.: Simultaneous iteration for variational inequalities over common solutions for finite families of nonlinear problems. J. Nonlinear Sci. Appl. 11, 394-416 (2018) · Zbl 1438.47110 · doi:10.22436/jnsa.011.03.08
[5] Chuang, C.S., Lin, L.J., Yu, Z.T.: Mathematical programming over the solution set of the minimization problem for the sum of two convex functions. J. Nonlinear Convex Anal. 17, 2105-2118 (2016) · Zbl 1470.49018
[6] Goebel, K., Reich, S.: Uniform Convexity, Hyperbolic Geometry, and Nonexpansive Mappings. Marcel Dekker, New York (1984) · Zbl 0537.46001
[7] Bauschke, H.H., Combettes, P.L.: Convex Analysis and Monotone Operator Theory in Hilbert Spaces. Springer, Berlin (2011) · Zbl 1218.47001 · doi:10.1007/978-1-4419-9467-7
[8] Bargetz, C., Reich, S., Zalas, R.: Convergence properties of dynamic string averaging projection methods in the presence of perturbations. Numer. Algorithms 77, 185-209 (2018) · Zbl 1459.47023 · doi:10.1007/s11075-017-0310-4
[9] Bailon, J.B., Bruck, R.E., Reich, S.: On the asymptotic behavior of nonexpansive mappings and semigroups in Banach spaces. Huston J. Math. 4, 1-9 (1978) · Zbl 0396.47033
[10] Bruck, R.E., Reich, S.: Nonexpansive projections and resolvents of accretive operators in Banach spaces. Huston J. Math. 3, 459-470 (1977) · Zbl 0383.47035
[11] Combettes, P.L.: Solving monotone inclusions via compositions of nonexpansive averaged operators. Optimization 53, 475-504 (2004) · Zbl 1153.47305 · doi:10.1080/02331930412331327157
[12] Wang, Y., Xu, H.K.: Strong convergence for the proximal gradient methods. J. Nonlinear Convex Anal. 15, 581-593 (2014) · Zbl 1295.46058
[13] Browder, E.E.: Fixed point theorems for noncompact mappings in Hilbert spaces. Proc. Nat. Acad. Sci. USA 53, 1272-1276 (1965) · Zbl 0125.35801 · doi:10.1073/pnas.53.6.1272
[14] Ekeland, I., Temam, R.: Convex Analysis and Variational Problems. North Holland Publishing Company, Amsterdam (1976) · Zbl 0322.90046
[15] Takahashi, W.: Nonlinear Functional Analysis, Fixed Point Theory and Its Applications. Yokohama Publishers, Yokohama (2000) · Zbl 0997.47002
[16] Lee, G.M., Lin, L.J.: Variational inequalities over split equality fixed point sets of strongly quasinonexpansive mappings with applications. J. Nonlinear Convex Anal. 18, 1781-1800 (2017) · Zbl 1505.47070
[17] Yu, Z.T., Lin, L.J., Chuang, C.S.: Mathematical programing with multiple sets split monotone variational inclusion constraints. Fixed Point Theory Appl. 2014, 20 (2014) · Zbl 1390.47011 · doi:10.1186/1687-1812-2014-20
[18] Chang, S.S., Wang, L., Tang, Y.K., Wang, G.: Moudafi’s open question and simultaneous iterative algorithm for general split equality optimization. Fixed Point Theory Appl. 2014, 215 (2014) · Zbl 1345.47034 · doi:10.1186/1687-1812-2014-215
[19] Combettes, P.L., Wajs, V.R.: Signal recovery by proximal forward – backward splitting. Multiscale Model. Simul. 4, 1168-1200 (2005) · Zbl 1179.94031 · doi:10.1137/050626090
[20] Censor, Y., Elfving, T., Kopf, N., Bortfeld, T.: The multiple-sets split feasibility problem and its applications for inverse problems. Inverse Probl. 21, 2071-2084 (2005) · Zbl 1089.65046 · doi:10.1088/0266-5611/21/6/017
[21] Combettes, P.L., Bondon, P.: Hard constrained inconsistent signal feasibility problems. IEEE Trans. Signal Process 47, 2460-2468 (1999) · Zbl 0979.94016 · doi:10.1109/78.782189
[22] Commettes, P.L.: A block-iterative surrogate constraint splitting method for quadratic signal recovery. IEEE Trans. Signal Process 51, 1771-1782 (2003) · Zbl 1369.94121 · doi:10.1109/TSP.2003.812846
[23] Masad, E., Reich, S.: A note on the multiple-set convex set split feasibility problem in Hilbert space. J. Nonlinear Convex Anal. 8, 367-371 (2007) · Zbl 1171.90009
[24] Xu, H.K.: A variable Krasnosel’skiĭ-Mann algorithm and the multiple-set split feasibility problem. Inverse Probl. 22, 2021-2034 (2006) · Zbl 1126.47057 · doi:10.1088/0266-5611/22/6/007
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